import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase          =						get_tests_dir("""fixtures/test_sentencepiece.model""")

if is_torch_available():
	from transformers.models.mbart.modeling_mbart import shift_tokens_right

_UpperCAmelCase          =						250004
_UpperCAmelCase          =						250020





@require_sentencepiece
@require_tokenizers
class UpperCAmelCase		(   __A   ,			unittest.TestCase    ):


				'''simple docstring'''






				lowerCamelCase_        =   MBartaaTokenizer
				lowerCamelCase_        =   MBartaaTokenizerFast
				lowerCamelCase_        =   True
				lowerCamelCase_        =   True
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						super().setUp()

						# We have a SentencePiece fixture for testing
						A_						:							Any      = MBartaaTokenizer(lowercase						,      src_lang='en_XX'						,      tgt_lang='ro_RO'						,      keep_accents=lowercase   )
						tokenizer.save_pretrained(self.tmpdirname   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Optional[Any]      = '<s>'
						A_						:							int      = 0

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase   )						,      lowercase   )
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase   )						,      lowercase   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Union[str, Any]      = list(self.get_tokenizer().get_vocab().keys()   )

						self.assertEqual(vocab_keys[0]						,      '<s>'   )
						self.assertEqual(vocab_keys[1]						,      '<pad>'   )
						self.assertEqual(vocab_keys[-1]						,      '<mask>'   )
						self.assertEqual(len(lowercase   )						,      1_0_5_4   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						self.assertEqual(self.get_tokenizer().vocab_size						,      1_0_5_4   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							List[str]      = MBartaaTokenizer(lowercase						,      src_lang='en_XX'						,      tgt_lang='ro_RO'						,      keep_accents=lowercase   )

						A_						:							List[str]      = tokenizer.tokenize('This is a test'   )
						self.assertListEqual(lowercase						,      ['▁This', '▁is', '▁a', '▁t', 'est']   )

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(lowercase   )						,      [value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]						,      )

						A_						:							Union[str, Any]      = tokenizer.tokenize('I was born in 92000, and this is falsé.'   )
						self.assertListEqual(
						    lowercase						,      [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '9', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', 'é', '.']						,      )
						A_						:							int      = tokenizer.convert_tokens_to_ids(lowercase   )
						self.assertListEqual(
						    lowercase						,      [
						        value + tokenizer.fairseq_offset
						        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
						    ]						,      )

						A_						:							List[Any]      = tokenizer.convert_ids_to_tokens(lowercase   )
						self.assertListEqual(
						    lowercase						,      [SPIECE_UNDERLINE + 'I', SPIECE_UNDERLINE + 'was', SPIECE_UNDERLINE + 'b', 'or', 'n', SPIECE_UNDERLINE + 'in', SPIECE_UNDERLINE + '', '<unk>', '2', '0', '0', '0', ',', SPIECE_UNDERLINE + 'and', SPIECE_UNDERLINE + 'this', SPIECE_UNDERLINE + 'is', SPIECE_UNDERLINE + 'f', 'al', 's', '<unk>', '.']						,      )
				@slow
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Union[str, Any]      = {'input_ids': [[2_5_0_0_0_4, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 5_4_2_8, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 1_2_3_9_9, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 2_7_8_9, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 8_0_5, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [2_5_0_0_0_4, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [2_5_0_0_0_4, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=lowercase						,      model_name='facebook/mbart-large-50'						,      revision='d3913889c59cd5c9e456b269c376325eabad57e2'						,      )







				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						if not self.test_slow_tokenizer:
								# as we don't have a slow version, we can't compare the outputs between slow and fast versions
								return

						A_						:							Optional[int]      = (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
								with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
										A_						:							int      = self.rust_tokenizer_class.from_pretrained(lowercase						,      **lowercase   )
										A_						:							Optional[Any]      = self.tokenizer_class.from_pretrained(lowercase						,      **lowercase   )

										A_						:							int      = tempfile.mkdtemp()

										A_						:							str      = tokenizer_r.save_pretrained(lowercase   )
										A_						:							Dict      = tokenizer_p.save_pretrained(lowercase   )

										# Checks it save with the same files + the tokenizer.json file for the fast one
										self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files   )   )
										A_						:							int      = tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f   )
										self.assertSequenceEqual(lowercase						,      lowercase   )

										# Checks everything loads correctly in the same way
										A_						:							Optional[Any]      = tokenizer_r.from_pretrained(lowercase   )
										A_						:							Dict      = tokenizer_p.from_pretrained(lowercase   )

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
												self.assertTrue(hasattr(lowercase						,      lowercase   )   )
												# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
												# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

										shutil.rmtree(lowercase   )

										# Save tokenizer rust, legacy_format=True
										A_						:							Any      = tempfile.mkdtemp()

										A_						:							List[str]      = tokenizer_r.save_pretrained(lowercase						,      legacy_format=lowercase   )
										A_						:							List[Any]      = tokenizer_p.save_pretrained(lowercase   )

										# Checks it save with the same files
										self.assertSequenceEqual(lowercase						,      lowercase   )

										# Checks everything loads correctly in the same way
										A_						:							Any      = tokenizer_r.from_pretrained(lowercase   )
										A_						:							int      = tokenizer_p.from_pretrained(lowercase   )

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
												self.assertTrue(hasattr(lowercase						,      lowercase   )   )

										shutil.rmtree(lowercase   )

										# Save tokenizer rust, legacy_format=False
										A_						:							str      = tempfile.mkdtemp()

										A_						:							List[Any]      = tokenizer_r.save_pretrained(lowercase						,      legacy_format=lowercase   )
										A_						:							List[str]      = tokenizer_p.save_pretrained(lowercase   )

										# Checks it saved the tokenizer.json file
										self.assertTrue(any('tokenizer.json' in f for f in tokenizer_r_files   )   )

										# Checks everything loads correctly in the same way
										A_						:							Dict      = tokenizer_r.from_pretrained(lowercase   )
										A_						:							Dict      = tokenizer_p.from_pretrained(lowercase   )

										# Check special tokens are set accordingly on Rust and Python
										for key in tokenizer_pp.special_tokens_map:
												self.assertTrue(hasattr(lowercase						,      lowercase   )   )

										shutil.rmtree(lowercase   )





@require_torch
@require_sentencepiece
@require_tokenizers
class UpperCAmelCase		(   unittest.TestCase    ):


				'''simple docstring'''






				lowerCamelCase_        =   '''facebook/mbart-large-50-one-to-many-mmt'''
				lowerCamelCase_        =   [
				    ''' UN Chief Says There Is No Military Solution in Syria''',
				    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that "there is no military solution" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.''',
				]
				lowerCamelCase_        =   [
				    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
				    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'''
				    ''' pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi că noi arme nu vor'''
				    ''' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
				]
				lowerCamelCase_        =   [EN_CODE, 8_2_7_4, 1_2_7_8_7_3, 2_5_9_1_6, 7, 8_6_2_2, 2_0_7_1, 4_3_8, 6_7_4_8_5, 5_3, 1_8_7_8_9_5, 2_3, 5_1_7_1_2, 2]
				@classmethod
				def     lowerCAmelCase_  (		cls   ):



						"""simple docstring"""





						A_						:							MBartaaTokenizer      = MBartaaTokenizer.from_pretrained(
						    cls.checkpoint_name						,      src_lang='en_XX'						,      tgt_lang='ro_RO'   )
						A_						:							Any      = 1
						return cls
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']						,      2_5_0_0_0_1   )
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']						,      2_5_0_0_0_4   )
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']						,      2_5_0_0_2_0   )
						self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']						,      2_5_0_0_3_8   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Any      = self.tokenizer.batch_encode_plus(self.src_text   ).input_ids[0]
						self.assertListEqual(self.expected_src_tokens						,      lowercase   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						self.assertIn(lowercase						,      self.tokenizer.all_special_ids   )
						A_						:							Optional[int]      = [RO_CODE, 8_8_4, 9_0_1_9, 9_6, 9, 9_1_6, 8_6_7_9_2, 3_6, 1_8_7_4_3, 1_5_5_9_6, 5, 2]
						A_						:							Tuple      = self.tokenizer.decode(lowercase						,      skip_special_tokens=lowercase   )
						A_						:							Union[str, Any]      = self.tokenizer.decode(generated_ids[1:]						,      skip_special_tokens=lowercase   )
						self.assertEqual(lowercase						,      lowercase   )
						self.assertNotIn(self.tokenizer.eos_token						,      lowercase   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Optional[int]      = ['this is gunna be a long sentence ' * 2_0]
						assert isinstance(src_text[0]						,      lowercase   )
						A_						:							Union[str, Any]      = 1_0
						A_						:							Optional[int]      = self.tokenizer(lowercase						,      max_length=lowercase						,      truncation=lowercase   ).input_ids[0]
						self.assertEqual(ids[0]						,      lowercase   )
						self.assertEqual(ids[-1]						,      2   )
						self.assertEqual(len(lowercase   )						,      lowercase   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']   )						,      [2_5_0_0_5_3, 2_5_0_0_0_1]   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Tuple      = tempfile.mkdtemp()
						A_						:							List[str]      = self.tokenizer.fairseq_tokens_to_ids
						self.tokenizer.save_pretrained(lowercase   )
						A_						:							Tuple      = MBartaaTokenizer.from_pretrained(lowercase   )
						self.assertDictEqual(new_tok.fairseq_tokens_to_ids						,      lowercase   )
				@require_torch
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							int      = self.tokenizer(self.src_text						,      text_target=self.tgt_text						,      padding=lowercase						,      return_tensors='pt'   )
						A_						:							Dict      = shift_tokens_right(batch['labels']						,      self.tokenizer.pad_token_id   )

						# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
						assert batch.input_ids[1][0] == EN_CODE
						assert batch.input_ids[1][-1] == 2
						assert batch.labels[1][0] == RO_CODE
						assert batch.labels[1][-1] == 2
						assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]
				@require_torch
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Optional[Any]      = self.tokenizer(
						    self.src_text						,      text_target=self.tgt_text						,      padding=lowercase						,      truncation=lowercase						,      max_length=len(self.expected_src_tokens   )						,      return_tensors='pt'						,      )
						A_						:							Union[str, Any]      = shift_tokens_right(batch['labels']						,      self.tokenizer.pad_token_id   )

						self.assertIsInstance(lowercase						,      lowercase   )

						self.assertEqual((2, 1_4)						,      batch.input_ids.shape   )
						self.assertEqual((2, 1_4)						,      batch.attention_mask.shape   )
						A_						:							Tuple      = batch.input_ids.tolist()[0]
						self.assertListEqual(self.expected_src_tokens						,      lowercase   )
						self.assertEqual(2						,      batch.decoder_input_ids[0, 0]   )  # decoder_start_token_id
						# Test that special tokens are reset
						self.assertEqual(self.tokenizer.prefix_tokens						,      [EN_CODE]   )
						self.assertEqual(self.tokenizer.suffix_tokens						,      [self.tokenizer.eos_token_id]   )
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Optional[int]      = self.tokenizer(self.src_text						,      padding=lowercase						,      truncation=lowercase						,      max_length=3						,      return_tensors='pt'   )
						A_						:							int      = self.tokenizer(
						    text_target=self.tgt_text						,      padding=lowercase						,      truncation=lowercase						,      max_length=1_0						,      return_tensors='pt'   )
						A_						:							List[Any]      = targets['input_ids']
						A_						:							Union[str, Any]      = shift_tokens_right(lowercase						,      self.tokenizer.pad_token_id   )

						self.assertEqual(batch.input_ids.shape[1]						,      3   )
						self.assertEqual(batch.decoder_input_ids.shape[1]						,      1_0   )







				@require_torch
				def     lowerCAmelCase_  (		self   ):



						"""simple docstring"""





						A_						:							Optional[int]      = self.tokenizer._build_translation_inputs(
						    'A test'						,      return_tensors='pt'						,      src_lang='en_XX'						,      tgt_lang='ar_AR'   )

						self.assertEqual(
						    nested_simplify(lowercase   )						,      {
						        # en_XX, A, test, EOS
						        'input_ids': [[2_5_0_0_0_4, 6_2, 3_0_3_4, 2]],
						        'attention_mask': [[1, 1, 1, 1]],
						        # ar_AR
						        'forced_bos_token_id': 2_5_0_0_0_1,
						    }						,      )







import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin





class UpperCAmelCase		(   __A   ,			__A   ,			__A    ):


				'''simple docstring'''






				@register_to_config
				def __init__(		self						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase						,      lowercase = False						,      ):



						"""simple docstring"""





						super().__init__()

						A_						:							Optional[int]      = nn.Embedding(lowercase						,      lowercase   )

						A_						:							Any      = nn.Embedding(lowercase						,      lowercase   )
						A_						:							int      = False

						A_						:							Tuple      = nn.Dropout(p=lowercase   )

						A_						:							List[Any]      = TaConfig(
						    vocab_size=lowercase						,      d_model=lowercase						,      num_heads=lowercase						,      d_kv=lowercase						,      d_ff=lowercase						,      dropout_rate=lowercase						,      feed_forward_proj=lowercase						,      is_decoder=lowercase						,      is_encoder_decoder=lowercase						,      )

						A_						:							List[str]      = nn.ModuleList()
						for lyr_num in range(lowercase   ):
								A_						:							Dict      = TaBlock(lowercase   )
								self.encoders.append(lowercase   )

						A_						:							Any      = TaLayerNorm(lowercase   )
						A_						:							Optional[int]      = nn.Dropout(p=lowercase   )







				def     lowerCAmelCase_  (		self						,      lowercase						,      lowercase   ):



						"""simple docstring"""





						A_						:							Any      = self.token_embedder(lowercase   )

						A_						:							List[Any]      = encoder_input_tokens.shape[1]
						A_						:							int      = torch.arange(lowercase						,      device=encoder_input_tokens.device   )
						x += self.position_encoding(lowercase   )

						A_						:							Dict      = self.dropout_pre(lowercase   )

						# inverted the attention mask
						A_						:							List[Any]      = encoder_input_tokens.size()
						A_						:							Dict      = self.get_extended_attention_mask(lowercase						,      lowercase   )

						for lyr in self.encoders:
								A_						:							List[str]      = lyr(lowercase						,      lowercase   )[0]
						A_						:							Optional[int]      = self.layer_norm(lowercase   )

						return self.dropout_post(lowercase   ), encoder_inputs_mask






